• DocumentCode
    3740399
  • Title

    The Development of Normative Autonomous Agents: An Approach

  • Author

    Marx Viana;Paulo Alencar;Donald Cowan; Guimar?es;Francisco Cunha;Carlos Lucena

  • Author_Institution
    Pontifical Catholic Univ. - PUC-Rio, Rio de Janeiro, Brazil
  • Volume
    2
  • fYear
    2015
  • Firstpage
    9
  • Lastpage
    16
  • Abstract
    Open multi-agent systems (MASs) act as societies in which autonomous and heterogeneous agents can work towards similar or different goals. In order to cope with the heterogeneity, autonomy and diversity of interests among the different agents in the society, open MASs establish a set of behavioral norms that is used as a mechanism to ensure a state of cooperation among agents. Such norms regulate the behavior of the agents by defining obligations, permissions and prohibitions. Fulfillment of a norm may be encouraged through a reward while violation of a norm may be discouraged through punishment. Although norms are promising mechanisms to regulate an agent´s behavior, we should note that each agent is an autonomous entity that is free to fulfill or violate each associated norm. Thus, agents can use different strategies when deciding to achieve their goals including whether to comply with their associated norms. Agents might choose to achieve their goals while ignoring their norms, thus overlooking the rewards or punishments they may receive. In contrast agents may choose to comply with all the norms although some of their goals may not be achieved. In this context, this paper proposes a framework for simulation of normative agents providing a basis for understanding the impacts of norms on agents.
  • Keywords
    "Multi-agent systems","Context","Software agents","Cultural differences","Context modeling","Cognition","Java"
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015 IEEE / WIC / ACM International Conference on
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2015.197
  • Filename
    7397307